Rebuttal from Ryan L. Hoiland and Philip N. Ainslie
Bibliographic record
Abstract
Brothers & Zhang (2016) provide a relevant CrossTalk discussion on the measurement of middle cerebral artery (MCA) diameter during alterations in arterial blood pressure (ABP) and gases. While in support of a constant MCA diameter, they nonetheless judiciously acknowledge that several previous studies indicating a constant MCA diameter, specifically during alterations in arterial blood gases, are confounded by subject co-morbidities, anesthesia, and/or suffer from poor resolution (1.5 T MRI) (Schreiber et al. 2000; Serrador et al. 2000). They speculate that elevations in ABP and the associated autoregulatory response concurrent to hypercapnia may explain the increases in diameter reported by the more recent and higher resolution MRI studies (3 and 7 T) assessing MCA diameter (Verbree et al. 2014; Coverdale et al. 2014). The rationale for this hypothesis is unclear as the available data in humans indicate an increase in ABP will increase cerebral vascular resistance in large cerebral arteries (Liu et al. 2013; Warnert et al. 2016). Collectively, these findings indicate that any engagement of autoregulatory mechanisms would more likely lead to an underestimation of vasodilatation, not overestimation. In their discussion of arterial blood gases, Brothers & Zhang fail to discuss the potential for hypoxia-induced vasomotion of the MCA. Previous study has indicated MCA dilatation in hypoxia (Wilson et al. 2011), in addition to more recent evidence that continues to highlight a tendency for increased MCA diameter (Sagoo et al. 2016). Overall there is a strong body of data supporting hypoxia-induced dilatation at the level of the MCA. It is noted by Brothers & Zhang that the study by Serrador et al. (2000) provides insight into MCA diameter during mild hypotension; however, a statistical change in BP did not occur during their simulated orthostasis trial (see Table 2 in Serrador et al. 2000). This renders the study by Giller et al. (1993) the only one to date that has directly imaged MCA diameter during alterations in ABP. Thus, while it remains difficult to definitively conclude the effect of ABP on MCA diameter, a large body of evidence now supports the notion that MCA diameter does change during alterations in arterial blood gases. Although we acknowledge that much utility still exists in the employment of transcranial Doppler ultrasound, we encourage the complimentary addition of multi-modal imaging to provide important new insight into cerebrovascular regulation in humans. Readers are invited to give their views on this and the accompanying CrossTalk articles in this issue by submitting a brief (250 word) comment. Comments may be submitted up to 6 weeks after publication of the article, at which point the discussion will close and the CrossTalk authors will be invited to submit a 'Last Word'. Please email your comment, including a title and a declaration of interest, to jphysiol@physoc.org. Comments will be moderated and accepted comments will be published online only as 'supporting information' to the original debate articles once discussion has closed. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. The authors declare no conflict of interest, financial or otherwise. Both authors have approved the final version of the manuscript and agree to be accountable for all aspects of the work. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.246 | 0.194 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".